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Bie12 Machine Learning Ops Engineer
hace 2 meses
Description Context:Would you like to work in a dynamic, international, technological environment, helping build something great from the ground up?
Following the Admiral Group Business Strategy, Admiral EU has launched an ambitious Data & Analytics (D&A) initiative to build strong foundations in terms of skills, governance, and technology.
In many areas of our business, data is essential to better understand the challenges that we face to make sound strategic and operational decisions.
We have been delivering business value from Big Data and Machine Learning for a few years, and we now seek to industrialize and automate the whole D&A value chain.
We want to minimize the time it takes to deploy our models so we can extract value faster and we would like to onboard skilled and motivated candidates like youRole Description:We are looking for a technical expert with a proven track record in Machine Learning Operations.
You will lead the development and implementation of technical MLOps best practices and influence an international cohort of data scientists towards adoption.
At a relational level, you will maintain direct interaction with the Advanced Analytics team to influence the modeling process from start to finish, as well as with the Data Development Engineers team to optimize flows.What do we offer?Great opportunities for growth and professional development.Although our offices are in Sevilla, we have a Remote First policy, adapting your day to your needs.Flexible working hours, with 25 days of working vacation per year.Participation in the company's share system.And many other things that make us the 2nd best company to work for in Spain in 2023, according to Great Place To Work SpainRequirements:This is youEssential requirements:Mid-senior professional with at least 4 years of experience in a similar role.Cloud Computing: in-depth expertise of AWS Sagemaker.Machine Learning: hands-on development of end-to-end data science workflows.DevOps: proven experience in CI/CD, automated testing, and software engineering principles.Infrastructure as code: proficient in tools like Terraform, CDK, or equivalent to provision resources.Monitoring: familiar with best practices on logging, monitoring, and observability.Experience influencing Data scientists to adopt the ML OPS framework.Fluency in working English.Residence in Spain.Desirable requirements:Vendor relationship management.Experience mentoring junior team members.Able to communicate complex concepts to a wide range of non-technical stakeholders.Location:Hybrid#J-18808-Ljbffr
